Abstract
Specific cell-cell interactions enable the complex metabolic tasks associated with natural microbial communities and facilitates their improved adaptation to environmental changes when compared to monocultures. Understanding these interactions can help resolve many of the underlying mechanisms regulating these complex microbial ecosystems and supply novel insights for various applications. However, the complexity of microbial interactions makes it difficult to evaluate them individually. However, droplet-based microfluidic methods can be used to compartmentalize individual responses to specific conditions in a massively parallel manner allowing for evaluations at a single-cell resolution. Moreover, individual droplets can be withdrawn from these systems without washing or dilution and can thus be used to determine the impact of specific substances used in intercellular interactions via further analysis such as next-generation sequencing or mass spectrometry. In this review, we summarized the recent progress around droplet-based microfluidic technologies for phenotypic characterization and screening using cell-cell interaction, which continues to diversify over time expanding its application to a variety of topics.
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References
Brenner, K., L. You, and F. H. Arnold (2008) Engineering microbial consortia: a new frontier in synthetic biology. Trends Biotechnol. 26: 483–489.
Kehe, J., A. Kulesa, A. Ortiz, C. M. Ackerman, S. G. Thakku, D. Sellers, S. Kuehn, J. Gore, J. Friedman, and P. C. Blainey (2019) Massively parallel screening of synthetic microbial communities. Proc. Natl. Acad. Sci. U. S. A. 116: 12804–12809.
Zhou, K., K. Qiao, S. Edgar, and G. Stephanopoulos (2015) Distributing a metabolic pathway among a microbial consortium enhances production of natural products. Nat. Biotechnol. 33: 377–383.
Li, L., C. Yang, W. Lan, S. Xie, C. Qiao, and J. Liu (2008) Removal of methyl parathion from artificial off-gas using a bioreactor containing a constructed microbial consortium. Environ. Sci. Technol. 42: 2136–2141.
Caballero, S., S. Kim, R. A. Carter, I. M. Leiner, B. Sušac, L. Miller, G. J. Kim, L. Ling, and E. G. Pamer (2017) Cooperating commensals restore colonization resistance to vancomycin-resistant Enterococcus faecium. Cell Host Microbe. 21: 592–602.e4.
Hsu, R. H., R. L. Clark, J. W. Tan, J. C. Ahn, S. Gupta, P. A. Romero, and O. S. Venturelli (2019) Microbial interaction network inference in microfluidic droplets. Cell Syst. 9: 229–242.e4.
Burmeister, A., F. Hilgers, A. Langner, C. Westerwalbesloh, Y. Kerkhoff, N. Tenhaef, T. Drepper, D. Kohlheyer, E. von Lieres, S. Noack, and A. Grünberger (2018) A microfluidic co-cultivation platform to investigate microbial interactions at defined microenvironments. Lab. Chip. 19: 98–110.
Hengoju, S., M. Tovar, D. Man, S. Buchheim, and M. A. Rosenbaum (2020) Droplet microfluidics for microbial biotechnology. Adv. Biochem. Eng. Biotechnol. Advance online publication. https://doi.org/10.1007/10_2020_140
Mitri, S. and K. R. Foster (2013) The genotypic view of social interactions in microbial communities. Annu. Rev. Genet. 47: 247–273.
Momeni, B., L. Xie, and W. Shou (2017) Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions. Elife. 6: e25051.
Demain, A. L. and S. Sanchez (2009) Microbial drug discovery: 80 years of progress. J. Antibiot. (Tokyo) 62: 5–16.
Vo, T., S. B. Shah, J. S. Choy, and X. Luo (2020) Chemotropism among populations of yeast cells with spatiotemporal resolution in a biofabricated microfluidic platform. Biomicrofluidics. 14: 014108.
Saeys, Y., S. Van Gassen, and B. N. Lambrecht (2016) Computational flow cytometry: helping to make sense of high-dimensional immunology data. Nat. Rev. Immunol. 16: 449–462.
Kaminski, T. S., O. Scheler, and P. Garstecki (2016) Droplet microfluidics for microbiology: techniques, applications and challenges. Lab. Chip. 16: 2168–2187.
Dai, J., S. H. Yoon, H. Y. Sim, Y. S. Yang, T. K. Oh, J. F. Kim, and J. W. Hong (2013) Charting microbial phenotypes in multiplex nanoliter batch bioreactors. Anal. Chem. 85: 5892–5899.
Min, S. K., B. M. Lee, J. H. Hwang, S. H. Ha, and H. S. Shin (2012) Mathematical analysis of colonial formation of embryonic stem cells in microfluidic system. Korean J. Chem. Eng. 29: 392–395.
Moore, T. I., H. Tanaka, H. J. Kim, N. L. Jeon, and T.-M. Yi (2013) Yeast G-proteins mediate directional sensing and polarization behaviors in response to changes in pheromone gradient direction. Mol. Biol. Cell 24: 521–534.
Jo, M. C., W. Liu, L. Gu, W. Dang, and L. Qin (2015) High-throughput analysis of yeast replicative aging using a microfluidic system. Proc. Natl. Acad. Sci. U. S. A. 112: 9364–9369.
Taylor, R. J., D. Falconnet, A. Niemistö, S. A. Ramsey, S. Prinz, I. Shmulevich, T. Galitski, and C. L. Hansen (2009) Dynamic analysis of MAPK signaling using a high-throughput microfluidic single-cell imaging platform. Proc. Natl. Acad. Sci. U. S. A. 106: 3758–3763.
Paliwal, S., P. A. Iglesias, K. Campbell, Z. Hilioti, A. Groisman, and A. Levchenko (2007) MAPK-mediated bimodal gene expression and adaptive gradient sensing in yeast. Nature. 446: 46–51.
Lee, S. S., P. Horvath, S. Pelet, B. Hegemann, L. P. Lee, and M. Peter (2012) Quantitative and dynamic assay of single cell chemotaxis. Integr. Biol. (Camb.) 4: 381–390.
Moore, T. I., C.-S. Chou, Q. Nie, N. L. Jeon, and T.-M. Yi (2008) Robust spatial sensing of mating pheromone gradients by yeast cells. PLoS One. 3: e3865.
Jin, S. H., S. S. Lee, B. Lee, S.-G. Jeong, M. Peter, and C.-S. Lee (2017) Programmable static droplet array for the analysis of cell-cell communication in a confined microenvironment. Anal. Chem. 89: 9722–9729.
Park, J., A. Kerner, M. A. Burns, and X. N. Lin (2011) Microdroplet-enabled highly parallel co-cultivation of microbial communities. PLoS One. 6: e17019.
Hansen, S. K., P. B. Rainey, J. A. J. Haagensen, and S. Molin (2007) Evolution of species interactions in a biofilm community. Nature. 445: 533–536.
Lidstrom, M. E. and M. C. Konopka (2010) The role of physiological heterogeneity in microbial population behavior. Nat. Chem. Biol. 6: 705–712.
Wang, M., A. L. Schaefer, A. A. Dandekar, and E. P. Greenberg (2015) Quorum sensing and policing of Pseudomonas aeruginosa social cheaters. Proc. Natl. Acad. Sci. U. S. A. 112: 2187–2191.
Jang, S., B. Lee, H.-H. Jeong, S. H. Jin, S. Jang, S. G. Kim, G. Y. Jung, and C.-S. Lee (2016) On-chip analysis, indexing and screening for chemical producing bacteria in a microfluidic static droplet array. Lab. Chip. 16: 1909–1916.
Jeong, H.-H., S. H. Jin, B. J. Lee, T. Kim, and C.-S. Lee (2015) Microfluidic static droplet array for analyzing microbial communication on a population gradient. Lab. Chip. 15: 889–899.
Jeong, H.-H., B. Lee, S. H. Jin, S.-G. Jeong, and C.-S. Lee (2016) A highly addressable static droplet array enabling digital control of a single droplet at pico-volume resolution. Lab. Chip. 16: 1698–1707.
Sun, M., S. S. Bithi, and S. A. Vanapalli (2011) Microfluidic static droplet arrays with tuneable gradients in material composition. Lab. Chip. 11: 3949–3952.
Agresti, J. J., E. Antipov, A. R. Abate, K. Ahn, A. C. Rowat, J.-C. Baret, M. Marquez, A. M. Klibanov, A. D. Griffiths, and D. A. Weitz (2010) Ultrahigh-throughput screening in drop-based microfluidics for directed evolution. Proc. Natl. Acad. Sci. U. S. A. 107: 4004–4009. (Erratum published 2010, Proc. Natl. Acad. Sci. U. S. A. 107: 6550)
Huang, M., Y. Bai, S. L. Sjostrom, B. M. Hallström, Z. Liu, D. Petranovic, M. Uhlén, H. N. Joensson, H. Andersson-Svahn, and J. Nielsen (2015) Microfluidic screening and whole-genome sequencing identifies mutations associated with improved protein secretion by yeast. Proc. Natl. Acad. Sci. U. S. A. 112: E4689–E4696.
Jeong, H.-H., D. Issadore, and D. Lee (2016) Recent developments in scale-up of microfluidic emulsion generation via parallelization. Korean J. Chem. Eng. 33: 1757–1766.
Wang, B. L., A. Ghaderi, H. Zhou, J. Agresti, D. A. Weitz, G. R. Fink, and G. Stephanopoulos (2014) Microfluidic high-throughput culturing of single cells for selection based on extracellular metabolite production or consumption. Nat. Biotechnol. 32: 473–478.
Sjostrom, S. L., Y. Bai, M. Huang, Z. Liu, J. Nielsen, H. N. Joensson, and H. Andersson Svahn (2014) High-throughput screening for industrial enzyme production hosts by droplet microfluidics. Lab. Chip. 14: 806–813.
Terekhov, S. S., I. V. Smirnov, A. V. Stepanova, T. V. Bobik, Y. A. Mokrushina, N. A. Ponomarenko, A. A. BelogurovJr., M. P. Rubtsova, O. V. Kartseva, M. O. Gomzikova, A. A. Moskovtsev, A. S. Bukatin, M. V. Dubina, E. S. Kostryukova, V. V. Babenko, M. T. Vakhitova, A. I. Manolov, M. V. Malakhova, M. A. Kornienko, A. V. Tyakht, A. A. Vanyushkina, E. N. Ilina, P. Masson, A. G. Gabibov, and S. Altman (2017) Microfluidic droplet platform for ultrahigh-throughput single-cell screening of biodiversity. Proc. Natl. Acad. Sci. U. S. A. 114: 2550–2555.
Jarosz, D. F., J. C. S. Brown, G. A. Walker, M. S. Datta, W. L. Ung, A. K. Lancaster, A. Rotem, A. Chang, G. A. Newby, D. A. Weitz, L. F. Bisson, and S. Lindquist (2014) Cross-kingdom chemical communication drives a heritable, mutually beneficial prion-based transformation of metabolism. Cell. 158: 1083–1093.
Scanlon, T. C., S. M. Dostal, and K. E. Griswold (2014) A high-throughput screen for antibiotic drug discovery. Biotechnol. Bioeng. 111: 232–243. (Erratum published 2019, Biotechnol. Bioeng. 116: 475)
Terekhov, S. S., I. V. Smirnov, M. V. Malakhova, A. E. Samoilov, A. I. Manolov, A. S. Nazarov, D. V. Danilov, S. A. Dubiley, I. A. Osterman, M. P. Rubtsova, E. S. Kostryukova, R. H. Ziganshin, M. A. Kornienko, A. A. Vanyushkina, O. N. Bukato, E. N. Ilina, V. V. Vlasov, K. V. Severinov, A. G. Gabibov, and S. Altman (2018) Ultrahigh-throughput functional profiling of microbiota communities. Proc. Natl. Acad. Sci. U. S. A. 115: 9551–9556.
Ohan, J., B. Pelle, P. Nath, J. H. Huang, B. Hovde, M. Vuyisich, A. E. Dichosa, and S. R. Starkenburg (2019) High-throughput phenotyping of cell-to-cell interactions in gel microdroplet pico-cultures. Biotechniques. 66: 218–224.
Saleski, T. E., A. R. Kerner, M. T. Chung, C. M. Jackman, A. Khasbaatar, K. Kurabayashi, and X. N. Lin (2019) Syntrophic co-culture amplification of production phenotype for high-throughput screening of microbial strain libraries. Metab. Eng. 54: 232–243.
Siedler, S., N. K. Khatri, A. Zsohár, I. Kjærbølling, M. Vogt, P. Hammar, C. F. Nielsen, J. Marienhagen, M. O. A. Sommer, and H. N. Joensson (2017) Development of a bacterial biosensor for rapid screening of yeast p-coumaric acid production. ACS Synth. Biol. 6: 1860–1869.
Meyer, A., R. Pellaux, S. Potot, K. Becker, H.-P. Hohmann, S. Panke, and M. Held (2015) Optimization of a whole-cell biocatalyst by employing genetically encoded product sensors inside nanolitre reactors. Nat. Chem. 7: 673–678.
Lee, H., J. I. Baek, S. J. Kim, K. K. Kwon, E. Rha, S.-J. Yeom, H. Kim, D.-H. Lee, D.-M. Kim, and S.-G. Lee (2020) Sensitive and rapid phenotyping of microbes with soluble methane monooxygenase using a droplet-based assay. Front. Bioeng. Biotechnol. 8: 358.
Kim, S., S. H. Jin, H. G. Lim, B. Lee, J. Kim, J. Yang, S. W. Seo, C.-S. Lee, and G. Y. Jung (2021) Synthetic cellular communication-based screening for strains with improved 3-hydroxypropionic acid secretion. Lab. Chip. 21: 4455–4463.
Tumarkin, E., L. Tzadu, E. Csaszar, M. Seo, H. Zhang, A. Lee, R. Peerani, K. Purpura, P. W. Zandstra, and E. Kumacheva (2011) High-throughput combinatorial cell co-culture using microfluidics. Integr. Biol. (Camb.) 3: 653–662.
Yanakieva, D., A. Elter, J. Bratsch, K. Friedrich, S. Becker, and H. Kolmar (2020) FACS-based functional protein screening via microfluidic co-encapsulation of yeast secretor and mammalian reporter cells. Sci. Rep. 10: 10182.
Fang, Y., T. H. Chu, M. E. Ackerman, and K. E. Griswold (2017) Going native: direct high throughput screening of secreted full-length IgG antibodies against cell membrane proteins. MAbs. 9: 1253–1261.
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This research was supported by the National Research Foundation of Korea grant (NRF-2019R1A2C2084631).
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Kim, S., Moon, J.H. & Jung, G.Y. Recent Progress in the Development of Droplet-based Microfluidic Technologies for Phenotypic Screening using Cell-cell Interactions. Biotechnol Bioproc E 28, 929–935 (2023). https://doi.org/10.1007/s12257-022-0081-1
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DOI: https://doi.org/10.1007/s12257-022-0081-1